Multi-Objective Machine Learning: 16 (Studies in Computational Intelligence, 16) - Image 1

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Springer Multi-Objective Machine Learning: 16 (Studies in Computational Intelligence, 16)

Name: Multi-Objective Machine Learning: 16 (Studies in Computational Intelligence, 16)
Brand: Springer
Price: 143.42 GBP
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AI & Machine Learning

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Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 3540306765
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 10 February 2006
Listed Since: 31 December 2006

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Springer Multi-Objective Machine Learning: 16 (Studies in Computational Intelligence, 16)

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